Method and apparatus for generating satellite tracking information in a compact format

ABSTRACT

Method and apparatus for creating a compact orbit model is described. Satellite tracking data is obtained having a first set of orbit terms that define a first orbit model. The satellite tracking data is formatted to form formatted data having a second set of orbit terms that define a second orbit model. A number of terms in the first set of orbit terms is greater than a number of terms in the second set of orbit terms.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.09/915,219, filed Jul. 25, 2001 now U.S. Pat. No. 6,651,000, whichincorporated by reference herein in its entirety.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to generating satellite trackinginformation for earth orbiting satellites. More specifically, theinvention relates to a method and apparatus for generating satellitetracking information in a first format (e.g., a compact ephemeris model)through a network or communications link, then representing thesatellite tracking information in a second format (e.g., a standardephemeris model) at a receiver.

2. Description of the Related Art

A positioning receiver for the Global Positioning System (GPS) usesmeasurements from several satellites to compute a position. The processof acquiring the GPS radio signal is enhanced in speed and sensitivityif the GPS receiver has prior access to a model of the satellite orbitand clock. This model is broadcast by the GPS satellites and is known asephemeris or ephemeris information. Each satellite broadcasts its ownephemeris once every 30 seconds. Once the GPS radio signal has beenacquired, the process of computing position requires the use of theephemeris information.

The broadcast ephemeris information is encoded in a 900 bit messagewithin the GPS satellite signal. It is transmitted at a rate of 50 bitsper second, taking 18 seconds in all for a complete ephemeristransmission. The broadcast ephemeris information is typically valid for2 to 4 hours into the future (from the time of broadcast). Before theend of the period of validity the GPS receiver must obtain a freshbroadcast ephemeris to continue operating correctly and produce anaccurate position. It is always slow (no faster than 18 seconds),frequently difficult, and sometimes impossible (in environments withvery low signal strengths), for a GPS receiver to download an ephemerisfrom a satellite. For these reasons it has long been known that it isadvantageous to send the ephemeris to a GPS receiver by some other meansin lieu of awaiting the transmission from the satellite. U.S. Pat. No.4,445,118, issued Apr. 24, 1984, describes a technique that collectssatellite orbit information at a GPS reference station, and transmitsthe information to the remote GPS receiver via a wireless transmission.This technique of providing the ephemeris, or equivalent data, to a GPSreceiver has become known as “Assisted-GPS”. Since the source ofephemeris in Assisted-GPS is the satellite signal, the ephemerisinformation remains valid for only a few hours. As such, the remote GPSreceiver must periodically connect to a source of ephemeris informationwhether that information is received directly from the satellite or froma wireless transmission. Without such a periodic update, the remote GPSreceiver will not accurately determine position.

Furthermore, the Assisted-GPS systems typically retransmit the entireephemeris message to the remote receiver. In many instances, bandwidthor packet size for the transmission of this message is not readilyavailable.

Therefore, there is a need for a method and apparatus for providingsatellite trajectory and clock information to a remote receiver in acompact form.

SUMMARY OF THE INVENTION

The present invention is a method and apparatus for generating satellitetracking data (STD), then transmitting the data to a remote receiver ina compact form. The STD is derived by receiving at one or more satellitetracking stations the signals from at least one satellite anddetermining satellite tracking information (STI) through signalprocessing or by extracting the ephemeris message from the receivedsignals. STI contains present satellite orbit trajectory data andsatellite clock information.

The STD is reformatted into a compact format and provided to a remotesatellite signal receiver via a network or communications system. Thereceiver converts the compact format into a standard format and uses theSTD to compute the position of the receiver. The satellite system mayinclude the global positioning system (GPS), GLONASS, GALILEO, or othersatellite systems that may use STD to enhance the performance of thereceiver.

BRIEF DESCRIPTION OF THE DRAWINGS

So that the manner in which the above recited features of the presentinvention can be understood in detail, a more particular description ofthe invention, briefly summarized above, may be had by reference toembodiments, some of which are illustrated in the appended drawings. Itis to be noted, however, that the appended drawings illustrate onlytypical embodiments of this invention and are therefore not to beconsidered limiting of its scope, for the invention may admit to otherequally effective embodiments.

FIG. 1 depicts a system for creating and distributing satellite trackingdata (STD) to remote GPS receivers;

FIG. 2 depicts a flow diagram of a method for forming the STD from thesatellite measurements made at satellite tracking stations;

FIG. 3 depicts a flow diagram of a method for forming a compact orbitmodel in accordance with the present invention; and

FIG. 4 depicts an example of compacting the orbit model, where two orbitmodel terms are compacted into a single term.

To facilitate understanding, identical reference numerals have beenused, wherever possible, to designate identical elements that are commonto the figures.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

FIG. 1 depicts a block diagram of a system 100 for creating anddistributing satellite tracking data (STD). The satellite system mayinclude the global positioning system (GPS), GLONASS, GALILEO, or othersatellite systems that may use STD to enhance the performance of thereceiver. The following disclosure uses GPS as an illustrative systemwithin which the invention operates. From the following disclosure,those skilled in the art will be able to practice the invention inconjunction with other satellite based positioning systems.

A network of GPS tracking stations 102 is used to collect measurementdata from the GPS satellites 104. Such a network is described in detailin U.S. Pat. No. 6,411,892, issued Jun. 25, 2002, which is incorporatedherein by reference. The network could comprise several trackingstations that collect satellite tracking information (STI) from all thesatellites in the constellation, or a few tracking stations, or a singletracking station that only collects STI for a particular region of theworld. An STD collection and computation server 106 collects andprocesses the measurement data (this measurement data is referred toherein as satellite tracking information (STI) that includes at leastone of: code phase measurements, carrier phase measurements, Dopplermeasurements, or ephemeris data). The ephemeris data may be the decodedephemeris message extracted from the GPS signal itself.

The server may create long term STD in accordance with the teachings ofU.S. Pat. No. 6,542,820, issued Apr. 1, 2003, or standard ephemerismessage data in accordance with the teachings of U.S. Pat. No.5,365,450, issued Nov. 15, 1994, both of which are incorporated hereinby reference. The server 106 may produce one or more of thefollowing: 1) accurate satellite tracking data (STD) (e.g., a trajectoryof each satellite and/or a clock offset measurement) during the datacollection period, 2) a prediction of the future STD of each satellite,and 3) models that match the future STD of each satellite.

The server 106 comprises a central processing unit (CPU) 118, supportcircuits 122, and memory 120. The CPU 118 may be any one of the manyCPUs available on the market to perform general computing.Alternatively, the CPU may be a specific purpose processor such as anapplication specific integrated circuit (ASIC) that is designed toprocess satellite tracking information. The support circuits 122 arewell known circuits such as clock circuits, cache, power supplies andthe like. The memory 120 may be read only memory, random access memory,disk drive storage, removable storage or any combination thereof. Thememory 120 stores executable software, e.g., STD software 124, that,when executed by the CPU 118, causes the system 100 to operate inaccordance with the present invention.

The set of satellite trajectory and clock data produced by the STDsoftware 124. The STD is stored in an STD database 108. A distributionserver 110 accesses the database 108 to gather the most recent set ofSTD, formats the data using the formatting software 111, and distributesthe formatted data to GPS devices 112 that require satellite orbitinformation. The software 111 produces a compact format, e.g., a compactephemeris model, in accordance with the present invention.

The distribution process may be implemented using some form of wirelesscommunications system 114, or over the Internet 116, or a combination ofboth, or by some other means of communication. Once the GPS devices 112have received the compact ephemeris model, they expand the model to aformat that is conventional for receiver. The compact ephemeris modeldistributed to the GPS devices may be in a similar format as thebroadcast ephemeris or may be some other model format that is defined bythe GPS device. Herein this orbit data is generally referred to as asatellite tracking model (STM). The loading of the STM into the GPSreceiver can be accomplished in many ways. Using the cradle for apersonal digital assistant (PDA), direct connection to a network, or awireless technology, such as Bluetooth or a cellular network, are a fewexamples of how the satellite data can be transferred to the receiver.The transmission is generally accomplished by broadcasting a compactmodel of the STD (or a compact model representing a portion of the STD)without knowledge of the specific location of the GPS receiver. As such,the distribution server does not require the GPS receiver to send anyinformation through the network to the distribution server.

Since GPS is a ranging system in and of itself, the data transmitted bythe GPS satellites can be used to determine the range, range-rate andclock offsets to the GPS satellites from a set of tracking stations.This set of observations generated by the tracking stations 102 is usedin the orbit determination process, and in the estimation of thesatellite clock characteristics. The set of monitoring stations 102could be a single station, a public network such as the ContinuouslyOperating Reference System (CORS), or a privately owned and/or operatednetwork.

FIG. 2 depicts a flow diagram of the process 200 of the presentinvention. The process 200 begins at step 202, wherein the satellitemeasurements are collected at the tracking stations. At step 204, thesatellite trajectory data (STD) is computed or extracted from thesatellite signals. The STD is then stored at step 206 in the STDdatabase. At step 208, the database is accessed and the formattingsoftware is executed to convert the formatting of the accessed STD. Theformatted STD is output as the compact model at step 210.

One embodiment of the invention formats the STD as a subset of thestandard ephemeris parameters defined in ICD-GPS-200c. Fitting the STDto the desired compact orbit model can be accomplished in a number ofmathematical methods. The preferred embodiment is a least-squares fit ofthe orbit model parameters to the trajectory data. Other methods, suchas Kalman filters or other estimators can also be used to obtain theorbit model parameters that best fit the trajectory data. Thesetechniques of fitting data to orbit models are well known to peopleskilled in the art of orbit determination and orbit modeling.

The least squares technique provides an optimal fit of the trajectorydata to the model trajectory formed from the compact orbit modelparameters. FIG. 3 depicts a flow diagram of a method of generating anorbit model using a least squares estimation technique.

At step 302, the STD for the desired time interval is extracted from theSTD database. The orbit model parameters are initialized to the orbitmodel values obtained by a similar process for the previous interval.This guarantees that the initial orbit model parameters are a good fitat least for the beginning of the desired time interval. The rest of theprocess 300 will ensure that the parameters are adjusted so that theybecome a good fit for the entire time interval.

In the preferred embodiment there are 15 orbital parameters to beadjusted:

Square root of semi-major axis (meterŝ½)

Eccentricity (dimensionless)

Amplitude of sine harmonic correction term to the orbit radius (meters)

Amplitude of cosine harmonic correction term to the orbit radius(meters)

Mean motion difference from computed value (radians/sec)

Mean anomaly at reference time (radians) Amplitude of cosine harmoniccorrection term to the argument of latitude (radians)

Amplitude of sine harmonic correction term to the argument of latitude(radians)

Amplitude of cosine harmonic correction term to the angle of inclination(radians)

Amplitude of sine harmonic correction term to the angle of inclination(radians)

Longitude of ascending node of orbit plane at weekly epoch (radians)

Inclination angle at reference time (radians)

Rate of inclination angle (radians/sec)

Argument of perigee (radians)

Rate of right ascension (radians/sec)

At step 303, some of the terms in the 15 term set are set to zero. Theterms that are selected are the 6 harmonic terms such that there are 9remaining parameters. This approach is particularly useful whenbandwidth and/or packet size is limited in the communication link thatwill be used to convey the orbit model to the satellite signal receiver,e.g., the remote GPS receiver. The subset of 9 parameters, by settingall harmonic terms in the model to zero, is:

Square root of semi-major axis (meterŝ½)

Eccentricity (dimensionless)

Mean motion difference from computed value (radians/sec)

Mean anomaly at reference time (radians)

Longitude of ascending node of orbit plane at weekly epoch (radians)

Inclination angle at reference time (radians)

Rate of inclination angle (radians/sec)

Argument of perigee (radians)

Rate of right ascension (radians/sec)

The receiver can then reconstruct a standard ephemeris model by settingthe “missing” harmonic terms to zero. In essence, the receiver reformatsthe STD for processing by the receiver circuits.

As an example of the method of generating the compact model, considerFIG. 4, which shows, for simplicity, just two terms of an orbit 400: anorbital radius (A), and a radial harmonic term (r). For this simpleexample, these two terms form the non-compact model, wherein the orbitis described by a circle of radius (A) plus a harmonic perturbation (r).To produce a more compact model that fits the actual orbit over aninterval 402, the method of the invention removes the harmonic term(i.e., sets the term (r) to zero) and increases the orbital radius (A)to a larger value (A1). The compact model is an orbit described by acircle with radius A1. If an application requires a non-compact orbitmodel, then the compact model (A1) can be represented as a non-compactmodel by specifying a harmonic term (r1) equal to zero. This compactmodel will fit the original orbit, over an interval 402, with a smallerror.

In the preferred embodiment, 6 harmonic terms are removed from the15-parameter model, and the other 9 terms are adjusted by process 300that is analogous to the example 400 to provide a compact model that isaccurate over a pre-defined interval. By adjusting the 9 remaining termsof an orbit model, while “zeroing” 6 harmonic terms, the compact modelcan be made accurate over a period of time such that a GPS receiver thatrelies on a compact model to compute position would compute a locationthat is no more than 2 meters less accurate than if the receiver used afull orbit model to compute position.

There are many alternative embodiments that will be readily apparent tothose skilled in the art, such as removing more or fewer terms beforeadjusting the remaining terms, setting removed terms to some value otherthan zero, and defining new terms that model the orbit.

Returning to FIG. 3, at step 304, the orbit model is used to predictwhat the trajectory would be, the predicted data is denoted the “ModelTrajectory Data” (MTD). If the model were perfect, the MTD wouldcoincide exactly with the STD. At step 306, the MTD and STD are comparedto see how closely the orbit model fits the orbit data. In the preferredembodiment, the comparison step 306 is performed by summing the squaresof the differences between each trajectory point in the STD and thecorresponding point in the MTD, and comparing the resulting sum to athreshold. If the fit is “good”, the model parameters are deemed “good”and the process stops at step 310. If the fit is not good then the modelparameters are adjusted at step 308. There are many techniques wellknown in the art for adjusting model parameters to fit data. Steps 304,306 and 308 are repeated until the model parameters are found that fitthe STD well.

There are a large number of alternative embodiments to reduce the sizeof the data, i.e., compacting the STD, while still providing a modelthat fits the STD, including:

Removing parameters from the model, and replacing them with a constant,such as zero—as done above—or some other predetermined value, which iseither stored in the Remote GPS Receiver, or occasionally sent to thereceiver. The predetermined value may be determined by a GPS almanacstored at both the receiver, and the distribution server.

The resolution of the parameters may be restricted in the process 300,this too reduces the amount of data that must be sent to the mobile GPSreceiver.

Parameters, which are similar among two or more satellites, may berepresented as a master value plus a delta, where the delta requiresfewer bits to encode; an example of this is the parameter Eccentricity,which changes very little among different GPS satellites.

Some of these approaches reduce the ability of the model to fit the dataover a period of time (e.g., four hours). In this case, the fit intervalmay be reduced (e.g. to two hours) to compensate. The accuracy of fit ofthe model can be traded off against the period of time over which themodel is valid.

While the foregoing is directed to embodiments of the present invention,other and further embodiments of the invention may be devised withoutdeparting from the basic scope thereof, and the scope thereof isdetermined by the claims that follow.

What is claimed is:
 1. A method of creating a compact orbit model,comprising: obtaining satellite tracking data having a first set oforbit terms that define a first orbit model; and formatting saidsatellite tracking data to form formatted data having a second set oforbit terms that define a second orbit model, where a number of terms insaid first set of orbit terms is greater than a number of terms in saidsecond set of orbit terms.
 2. The method of claim 1, wherein theobtaining step comprises: receiving satellite signals from a least onereceiving station; and extracting measurement data from said satellitesignals; and forming the satellite tracking data in response to themeasurement data.
 3. The method of claim 2, wherein the measurement datacomprises at least one of: code phase measurements, carrier phasemeasurements, Doppler measurements, and satellite ephemeris data.
 4. Themethod of claim 1, wherein said satellite tracking data comprises atleast one of a satellite orbit model or a satellite clock model.
 5. Themethod of claim 1, wherein said satellite tracking data comprises atleast one of: data representative of a satellite orbit model, an orbitmodel, and data representative of a satellite clock model.
 6. The methodof claim 1, where said terms in said second orbit model require fewerbits to encode it than said terms in said first orbit model.
 7. Themethod of claim 1, wherein said satellite signals are GPS signals. 8.The method of claim 1, where an accuracy of the data in said secondorbit model is increased by decreasing a time interval represented bysaid formatted data defining said second orbit model.
 9. The method ofclaim 1, wherein said formatting step further comprises: zeroing aplurality of terms in said first set of orbit terms.
 10. The method ofclaim 9, wherein said formatting step further comprises: adjusting aplurality of non-zero terms in said second set of orbit terms inresponse to the effects of zeroing terms in said first set of terms. 11.The method of claim 9, wherein the plurality of terms in said first setof orbit terms that are zeroed are harmonic terms.
 12. The method ofclaim 1, wherein said formatting step further comprises: replacing aplurality of terms in said first set of orbit terms with a constantvalue.
 13. The method of claim 12, wherein the constant value isdetermined in response to satellite almanac data.
 14. The method ofclaim 1, wherein said formatted data having said first set of orbitterms comprises parameters defined in ICD-GPS-200.
 15. The method ofclaim 1, wherein at least one term of said second set of orbit terms isdefined as a number with a lower resolution than a corresponding term insaid first set of orbit terms.
 16. A method of creating a compact orbitmodel, comprising: receiving satellite signals having satellite trackingdata from at least one receiving station; extracting at least a portionof the satellite tracking data from the satellite signals, where saidportion comprises a first set of orbit terms that define a first orbitmodel; and formatting said portion to form formatted data having asecond set of orbit terms that define a second orbit model, where anumber of terms in said first set of orbit terms is greater than anumber of terms in said second set of orbit terms.
 17. The method ofclaim 16, wherein said satellite tracking data comprises at least one ofa satellite orbit model or a satellite clock model.
 18. The method ofclaim 16, wherein said satellite tracking data comprises at least oneof: data representative of a satellite orbit model, an orbit model, anddata representative of a satellite clock model.
 19. The method of claim16, where said terms in said second orbit model require fewer bits toencode it than said terms in said first orbit model.
 20. The method ofclaim 16, wherein said satellite signals are GPS signals.
 21. The methodof claim 16, wherein said satellite tracking data comprises at least oneof code phase measurements, carrier phase measurements, Dopplermeasurements, and satellite ephemeris data.
 22. The method of claim 16,where an accuracy of the data in said second orbit model is increased bydecreasing a time interval represented by said formatted data definingsaid second orbit model.
 23. The method of claim 16, wherein saidformatting step further comprises: zeroing a plurality of terms in saidfirst set of orbit terms.
 24. The method of claim 23, wherein saidformatting step further comprises: adjusting a plurality of non-zeroterms in said second set of orbit terms in response to the effects ofzeroing terms in said first set of terms.
 25. The method of claim 23,wherein the plurality of terms in said first set of orbit terms that arezeroed are harmonic terms.
 26. The method of claim 16, wherein saidformatting step further comprises: replacing a plurality of terms insaid first set of orbit terms with a constant value.
 27. The method ofclaim 26, wherein the constant value is determined in response tosatellite almanac data.
 28. The method of claim 16, wherein saidformatted data having said first set of orbit terms comprises parametersdefined in ICD-GPS-200.
 29. The method of claim 16, wherein at least oneterm of said second set of orbit terms is defined as a number with alower resolution than a corresponding term in said first set of orbitterms.
 30. An apparatus for distributing compact satellite orbit models,comprising: a database for storing satellite tracking data having afirst set of terms that define a first orbit model; and means forformatting said satellite tracking data to form formatted data having asecond set of orbit terms that define a second orbit model, where anumber of terms in said first set of orbit terms is greater than anumber of terms in said second set of orbit terms.
 31. The apparatus ofclaim 30, further comprising: at least one satellite signal receiver forreceiving satellite signals from at least one satellite; means forextracting measurement data from said satellite signals; and means forforming the satellite tracking data in response to the measurement data.